1
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Elfer K, Gardecki E, Garcia V, Ly A, Hytopoulos E, Wen S, Hanna MG, Peeters DJE, Saltz J, Ehinger A, Dudgeon SN, Li X, Blenman KRM, Chen W, Green U, Birmingham R, Pan T, Lennerz JK, Salgado R, Gallas BD. Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models. Mod Pathol 2024; 37:100439. [PMID: 38286221 DOI: 10.1016/j.modpat.2024.100439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 12/14/2023] [Accepted: 01/21/2024] [Indexed: 01/31/2024]
Abstract
This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets. In an earlier work by other researchers, an annotation workflow and quality checklist for computational pathology annotations were proposed. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as the Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence (CLEARR-AI).
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Affiliation(s)
- Katherine Elfer
- United States Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland; National Institutes of Health, National Cancer Institute, Division of Cancer Prevention, Cancer Prevention Fellowship Program, Bethesda, Maryland.
| | - Emma Gardecki
- United States Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland
| | - Victor Garcia
- United States Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland
| | - Amy Ly
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | | | - Si Wen
- United States Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland
| | - Matthew G Hanna
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Dieter J E Peeters
- Department of Pathology, University Hospital Antwerp/University of Antwerp, Antwerp, Belgium; Department of Pathology, Sint-Maarten Hospital, Mechelen, Belgium
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York
| | - Anna Ehinger
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Laboratory Medicine, Lund University, Lund, Sweden
| | - Sarah N Dudgeon
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Xiaoxian Li
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Kim R M Blenman
- Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine and Yale Cancer Center, Yale University, New Haven, Connecticut; Department of Computer Science, School of Engineering and Applied Science, Yale University, New Haven, Connecticut
| | - Weijie Chen
- United States Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland
| | - Ursula Green
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia
| | - Ryan Birmingham
- United States Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia
| | - Tony Pan
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia
| | - Jochen K Lennerz
- Department of Pathology, Center for Integrated Diagnostics, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Roberto Salgado
- Division of Research, Peter Mac Callum Cancer Centre, Melbourne, Australia; Department of Pathology, GZA-ZNA Hospitals, Antwerp, Belgium
| | - Brandon D Gallas
- United States Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland
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2
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Sharrow AC, Ho M, Dua A, Buj R, Blenman KRM, Orsulic S, Buckanovich R, Aird KM, Wu L. Tumor-Associated Macrophages Expand Chemoresistant, Ovarian Cancer Stem-Like Cells. bioRxiv 2023:2023.07.17.549067. [PMID: 37503008 PMCID: PMC10370114 DOI: 10.1101/2023.07.17.549067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The persistence of ovarian cancer stem-like cells (OvCSCs) after chemotherapy resistance has been implicated in relapse. However, the ability of these relatively quiescent cells to produce the robust tumor regrowth necessary for relapse remains an enigma. Since normal stem cells exist in a niche, and tumor-associated macrophages (TAMs) are the highest abundance immune cell within ovarian tumors, we hypothesized that TAMs may influence OvCSC proliferation. To test this, we optimized OvCSC enrichment by sphere culture and in vitro polarization of monocytes to a TAM-like M2 phenotype. Using cocultures that permitted the exchange of only soluble factors, we found that M2 macrophages increased the proliferation of sphere cells. Longer-term exposure (5-7 days) to soluble TAM factors led to retention of some stem cell features by OvCSCs but loss of others, suggesting that TAMs may support an intermediate stemness phenotype in OvCSCs. Although TAM coculture decreased the percentage of OvCSCs surviving chemotherapy, it increased the overall number. We therefore sought to determine the influence of this interaction on chemotherapy efficacy in vivo and found that inhibiting macrophages improved chemotherapy response. Comparing the gene expression changes in OvCSCs cocultured with TAMs to publicly available patient data identified 34 genes upregulated in OvCSCs by exposure to soluble TAM factors whose expression correlates with outcome. Overall, these data suggest that TAMs may influence OvCSC proliferation and impact therapeutic response.
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3
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Fanucci KA, Bai Y, Pelekanou V, Nahleh ZA, Shafi S, Burela S, Barlow WE, Sharma P, Thompson AM, Godwin AK, Rimm DL, Hortobagyi GN, Liu Y, Wang L, Wei W, Pusztai L, Blenman KRM. Image analysis-based tumor infiltrating lymphocytes measurement predicts breast cancer pathologic complete response in SWOG S0800 neoadjuvant chemotherapy trial. NPJ Breast Cancer 2023; 9:38. [PMID: 37179362 PMCID: PMC10182981 DOI: 10.1038/s41523-023-00535-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 04/11/2023] [Indexed: 05/15/2023] Open
Abstract
We assessed the predictive value of an image analysis-based tumor-infiltrating lymphocytes (TILs) score for pathologic complete response (pCR) and event-free survival in breast cancer (BC). About 113 pretreatment samples were analyzed from patients with stage IIB-IIIC HER-2-negative BC randomized to neoadjuvant chemotherapy ± bevacizumab. TILs quantification was performed on full sections using QuPath open-source software with a convolutional neural network cell classifier (CNN11). We used easTILs% as a digital metric of TILs score defined as [sum of lymphocytes area (mm2)/stromal area(mm2)] × 100. Pathologist-read stromal TILs score (sTILs%) was determined following published guidelines. Mean pretreatment easTILs% was significantly higher in cases with pCR compared to residual disease (median 36.1 vs.14.8%, p < 0.001). We observed a strong positive correlation (r = 0.606, p < 0.0001) between easTILs% and sTILs%. The area under the prediction curve (AUC) was higher for easTILs% than sTILs%, 0.709 and 0.627, respectively. Image analysis-based TILs quantification is predictive of pCR in BC and had better response discrimination than pathologist-read sTILs%.
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Affiliation(s)
- Kristina A Fanucci
- Department of Internal Medicine Section of Medical Oncology and Yale Cancer Center, Yale School of Medicine, 333 Cedar St, New Haven, CT, 06520, USA
| | - Yalai Bai
- Department of Pathology, Yale School of Medicine, 310 Cedar St, New Haven, CT, 06520, USA
| | - Vasiliki Pelekanou
- Department of Pathology, Yale School of Medicine, 310 Cedar St, New Haven, CT, 06520, USA
- Bayer Pharmaceuticals, 245 First St Cambridge Science Center 100 and 200 Floors 1 and 2, Cambridge, MA, 02142, USA
| | - Zeina A Nahleh
- Department of Hematology/Oncology, Cleveland Clinic Florida, Maroone Cancer Center, 2950 Cleveland Clinic Blvd, Weston, FL, 33331, USA
| | - Saba Shafi
- Department of Pathology, Yale School of Medicine, 310 Cedar St, New Haven, CT, 06520, USA
- Department of Pathology, Ohio State University, 6100 Optometry Clinic & Health Sciences Faculty Office Building, 1664 Neil Avenue, Columbus, OH, 43210, USA
| | - Sneha Burela
- Department of Pathology, Yale School of Medicine, 310 Cedar St, New Haven, CT, 06520, USA
| | - William E Barlow
- SWOG Statistics and Data Management Center, 1730 Minor Avenue Suite 1900, Seattle, WA, 98101, USA
| | - Priyanka Sharma
- Department of Medical Oncology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS, 66160, USA
| | - Alastair M Thompson
- Section of Breast Surgery, 1 Baylor Plaza, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Andrew K Godwin
- Department of Medical Oncology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS, 66160, USA
| | - David L Rimm
- Department of Pathology, Yale School of Medicine, 310 Cedar St, New Haven, CT, 06520, USA
| | - Gabriel N Hortobagyi
- Department of Breast Medical Oncology, MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Yihan Liu
- Department of Biostatistics, Yale School of Public Health, 60 College Street, New Haven, CT, 06520, USA
| | - Leona Wang
- Department of Biostatistics, Yale School of Public Health, 60 College Street, New Haven, CT, 06520, USA
| | - Wei Wei
- Department of Biostatistics, Yale School of Public Health, 60 College Street, New Haven, CT, 06520, USA
| | - Lajos Pusztai
- Department of Internal Medicine Section of Medical Oncology and Yale Cancer Center, Yale School of Medicine, 333 Cedar St, New Haven, CT, 06520, USA
| | - Kim R M Blenman
- Department of Internal Medicine Section of Medical Oncology and Yale Cancer Center, Yale School of Medicine, 333 Cedar St, New Haven, CT, 06520, USA.
- Department of Computer Science, Yale School of Engineering and Applied Science, 17 Hillhouse Avenue, New Haven, CT, 06520, USA.
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Akingbesote ND, Owusu D, Liu R, Cartmel B, Ferrucci LM, Zupa M, Lustberg MB, Sanft T, Blenman KRM, Irwin ML, Perry RJ. A review of the impact of energy balance on triple-negative breast cancer. J Natl Cancer Inst Monogr 2023; 2023:104-124. [PMID: 37139977 DOI: 10.1093/jncimonographs/lgad011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 02/17/2023] [Accepted: 02/22/2023] [Indexed: 05/05/2023] Open
Abstract
Cancer cells cannot proliferate without sufficient energy to generate biomass for rapid cell division, as well as to fuel their functions at baseline. For this reason, many recent observational and interventional studies have focused on increasing energy expenditure and/or reducing energy intake during and after cancer treatment. The impact of variance in diet composition and in exercise on cancer outcomes has been detailed extensively elsewhere and is not the primary focus of this review. Instead, in this translational, narrative review we examine studies of how energy balance impacts anticancer immune activation and outcomes in triple-negative breast cancer (TNBC). We discuss preclinical, clinical observational, and the few clinical interventional studies on energy balance in TNBC. We advocate for the implementation of clinical studies to examine how optimizing energy balance-through changes in diet and/or exercise-may optimize the response to immunotherapy in people with TNBC. It is our conviction that by taking a holistic approach that includes energy balance as a key factor to be considered during and after treatment, cancer care may be optimized, and the detrimental effects of cancer treatment and recovery on overall health may be minimized.
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Affiliation(s)
- Ngozi D Akingbesote
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Department of Cellular & Molecular Physiology, Yale University, New Haven, CT, USA
| | - Dennis Owusu
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Department of Cellular & Molecular Physiology, Yale University, New Haven, CT, USA
- Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti Region, Ghana
| | - Ryan Liu
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Department of Cellular & Molecular Physiology, Yale University, New Haven, CT, USA
- Cedar Park High School, Cedar Park, TX, USA
| | - Brenda Cartmel
- Yale School of Public Health, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
| | - Leah M Ferrucci
- Yale School of Public Health, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
| | | | - Maryam B Lustberg
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
| | - Tara Sanft
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
| | - Kim R M Blenman
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
- Department of Computer Science, Yale University, New Haven, CT, USA
| | - Melinda L Irwin
- Yale School of Public Health, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
| | - Rachel J Perry
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Department of Cellular & Molecular Physiology, Yale University, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
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5
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Wall I, Boulat V, Shah A, Blenman KRM, Wu Y, Alberts E, Calado DP, Salgado R, Grigoriadis A. Leveraging the Dynamic Immune Environment Triad in Patients with Breast Cancer: Tumour, Lymph Node, and Peripheral Blood. Cancers (Basel) 2022; 14:4505. [PMID: 36139665 PMCID: PMC9496983 DOI: 10.3390/cancers14184505] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 11/29/2022] Open
Abstract
During the anti-tumour response to breast cancer, the primary tumour, the peripheral blood, and the lymph nodes each play unique roles. Immunological features at each site reveal evidence of continuous immune cross-talk between them before, during and after treatment. As such, immune responses to breast cancer are found to be highly dynamic and truly systemic, integrating three distinct immune sites, complex cell-migration highways, as well as the temporal dimension of disease progression and treatment. In this review, we provide a connective summary of the dynamic immune environment triad of breast cancer. It is critical that future studies seek to establish dynamic immune profiles, constituting multiple sites, that capture the systemic immune response to breast cancer and define patient-selection parameters resulting in more significant overall responses and survival rates for breast cancer patients.
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Affiliation(s)
- Isobelle Wall
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK
| | - Victoire Boulat
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK
- Immunity and Cancer Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Aekta Shah
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK
- Department of Pathology, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai 400012, India
| | - Kim R. M. Blenman
- Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine, Yale University, New Haven, CT 06510, USA
- Department of Computer Science, School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA
| | - Yin Wu
- Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK
- Peter Gorer Department of Immunobiology, School of Immunology & Microbial Sciences, King’s College London, London SE1 9RT, UK
- Centre for Inflammation Biology and Cancer Immunology, School of Immunology & Microbial Sciences, King’s College London, London SE1 9RT, UK
| | - Elena Alberts
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK
- Immunity and Cancer Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Dinis Pedro Calado
- Immunity and Cancer Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Roberto Salgado
- Department of Pathology, GZA-ZNA Hospitals, 2610 Antwerp, Belgium
- Division of Research, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia
| | - Anita Grigoriadis
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK
- Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK
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6
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Marczyk M, Qing T, O'Meara T, Yagahoobi V, Pelekanou V, Bai Y, Reisenbichler E, Cole KS, Li X, Gunasekharan V, Ibrahim E, Fanucci K, Wei W, Rimm DL, Pusztai L, Blenman KRM. Tumor immune microenvironment of self-identified African American and non-African American triple negative breast cancer. NPJ Breast Cancer 2022; 8:88. [PMID: 35869114 PMCID: PMC9307813 DOI: 10.1038/s41523-022-00449-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 06/20/2022] [Indexed: 02/06/2023] Open
Abstract
Differences in the tumor immune microenvironment may result in differences in prognosis and response to treatment in cancer patients. We hypothesized that differences in the tumor immune microenvironment may exist between African American (AA) and NonAA patients, due to ancestry-related or socioeconomic factors, that may partially explain differences in clinical outcomes. We analyzed clinically matched triple-negative breast cancer (TNBC) tissues from self-identified AA and NonAA patients and found that stromal TILs, PD-L1 IHC-positivity, mRNA expression of immune-related pathways, and immunotherapy response predictive signatures were significantly higher in AA samples (p < 0.05; Fisher's Exact Test, Mann-Whitney Test, Permutation Test). Cancer biology and metabolism pathways, TAM-M2, and Immune Exclusion were significantly higher in NonAA samples (p < 0.05; Permutation Test, Mann-Whitney Test). There were no differences in somatic tumor mutation burden. Overall, there is greater immune infiltration and inflammation in AA TNBC and these differences may impact response to immune checkpoint inhibitors and other therapeutic agents that modulate the immune microenvironment.
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Affiliation(s)
- Michal Marczyk
- Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland
- Yale Cancer Center, Yale University, New Haven, CT, USA
| | - Tao Qing
- Department of Internal Medicine, Section of Medical Oncology, Yale University, New Haven, CT, USA
| | - Tess O'Meara
- Department of Internal Medicine, Section of Medical Oncology, Yale University, New Haven, CT, USA
- Department of Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Vesal Yagahoobi
- Department of Pathology, Yale University, New Haven, CT, USA
| | - Vasiliki Pelekanou
- Department of Pathology, Yale University, New Haven, CT, USA
- Precision Medicine - Oncology, Translational Medical Oncology, Translational Medicine Early Development, Sanofi, Cambridge, MA, USA
| | - Yalai Bai
- Department of Pathology, Yale University, New Haven, CT, USA
| | | | - Kimberly S Cole
- Department of Pathology, Yale University, New Haven, CT, USA
- Sema4 Genomics, Branford, CT, USA
| | - Xiaotong Li
- Department of Computational Biology & Bioinformatics, Biological & Biomedical Sciences, Yale University, New Haven, CT, USA
| | - Vignesh Gunasekharan
- Yale Cancer Center, Yale University, New Haven, CT, USA
- Department of Internal Medicine, Section of Medical Oncology, Yale University, New Haven, CT, USA
| | - Eiman Ibrahim
- Department of Pharmacology, Yale University, New Haven, CT, USA
| | | | - Wei Wei
- Yale Cancer Center, Yale University, New Haven, CT, USA
- Department of Biostatistics, Yale University, New Haven, CT, USA
| | - David L Rimm
- Yale Cancer Center, Yale University, New Haven, CT, USA
- Department of Internal Medicine, Section of Medical Oncology, Yale University, New Haven, CT, USA
- Department of Pathology, Yale University, New Haven, CT, USA
| | - Lajos Pusztai
- Yale Cancer Center, Yale University, New Haven, CT, USA.
- Department of Internal Medicine, Section of Medical Oncology, Yale University, New Haven, CT, USA.
| | - Kim R M Blenman
- Yale Cancer Center, Yale University, New Haven, CT, USA.
- Department of Internal Medicine, Section of Medical Oncology, Yale University, New Haven, CT, USA.
- Department of Computer Science, Yale University, New Haven, CT, USA.
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7
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Hercules SM, Liu X, Bassey-Archibong BBI, Skeete DHA, Smith Connell S, Daramola A, Banjo AA, Ebughe G, Agan T, Ekanem IO, Udosen J, Obiorah C, Ojule AC, Misauno MA, Dauda AM, Egbujo EC, Hercules JC, Ansari A, Brain I, MacColl C, Xu Y, Jin Y, Chang S, Carpten JD, Bédard A, Pond GR, Blenman KRM, Manojlovic Z, Daniel JM. Analysis of the genomic landscapes of Barbadian and Nigerian women with triple negative breast cancer. Cancer Causes Control 2022; 33:831-841. [PMID: 35384527 PMCID: PMC9085672 DOI: 10.1007/s10552-022-01574-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 03/12/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype that disproportionately affects women of African ancestry (WAA) and is often associated with poor survival. Although there is a high prevalence of TNBC across West Africa and in women of the African diaspora, there has been no comprehensive genomics study to investigate the mutational profile of ancestrally related women across the Caribbean and West Africa. METHODS This multisite cross-sectional study used 31 formalin-fixed paraffin-embedded (FFPE) samples from Barbadian and Nigerian TNBC participants. High-resolution whole exome sequencing (WES) was performed on the Barbadian and Nigerian TNBC samples to identify their mutational profiles and comparisons were made to African American, European American and Asian American sequencing data obtained from The Cancer Genome Atlas (TCGA). Whole exome sequencing was conducted on tumors with an average of 382 × coverage and 4335 × coverage for pooled germline non-tumor samples. RESULTS Variants detected at high frequency in our WAA cohorts were found in the following genes NBPF12, PLIN4, TP53 and BRCA1. In the TCGA TNBC cases, these genes had a lower mutation rate, except for TP53 (32% in our cohort; 63% in TCGA-African American; 67% in TCGA-European American; 63% in TCGA-Asian). For all altered genes, there were no differences in frequency of mutations between WAA TNBC groups including the TCGA-African American cohort. For copy number variants, high frequency alterations were observed in PIK3CA, TP53, FGFR2 and HIF1AN genes. CONCLUSION This study provides novel insights into the underlying genomic alterations in WAA TNBC samples and shines light on the importance of inclusion of under-represented populations in cancer genomics and biomarker studies.
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Affiliation(s)
- Shawn M. Hercules
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
- African Caribbean Cancer Consortium, Philadelphia, PA USA
| | - Xiyu Liu
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | | | - Desiree H. A. Skeete
- African Caribbean Cancer Consortium, Philadelphia, PA USA
- grid.412886.10000 0004 0592 769XFaculty of Medical Sciences, University of the West Indies at Cave Hill, Bridgetown, Barbados
- grid.415521.60000 0004 0570 5165Department of Pathology, Queen Elizabeth Hospital, Bridgetown, Barbados
| | - Suzanne Smith Connell
- grid.412886.10000 0004 0592 769XFaculty of Medical Sciences, University of the West Indies at Cave Hill, Bridgetown, Barbados
- grid.415521.60000 0004 0570 5165Department of Radiation Oncology, Queen Elizabeth Hospital, Bridgetown, Barbados
- Present Address: Cancer Specialists Inc, Bridgetown, Barbados
| | - Adetola Daramola
- grid.411283.d0000 0000 8668 7085Department of Anatomic and Molecular Pathology, Lagos University Teaching Hospital, Lagos, Nigeria
| | - Adekunbiola A. Banjo
- grid.411283.d0000 0000 8668 7085Department of Anatomic and Molecular Pathology, Lagos University Teaching Hospital, Lagos, Nigeria
| | - Godwin Ebughe
- grid.413097.80000 0001 0291 6387Department of Pathology, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Thomas Agan
- grid.413097.80000 0001 0291 6387Department of Obstetrics & Gynaecology, College of Medical Sciences, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Ima-Obong Ekanem
- grid.413097.80000 0001 0291 6387Department of Pathology, College of Medical Sciences, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Joe Udosen
- grid.413097.80000 0001 0291 6387Division of General and Breast Surgery, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Christopher Obiorah
- grid.412738.bDepartment of Anatomical Pathology, University of Port Harcourt Teaching Hospital, Port Harcourt, Nigeria
| | - Aaron C. Ojule
- grid.412738.bDepartment of Chemical Pathology, University of Port Harcourt Teaching Hospital, Port Harcourt, Nigeria
| | - Michael A. Misauno
- grid.411946.f0000 0004 1783 4052Department of Surgery, Jos University Teaching Hospital, Jos, Nigeria
| | - Ayuba M. Dauda
- grid.411946.f0000 0004 1783 4052Department of Pathology, Jos University Teaching Hospital, Jos, Nigeria
| | | | - Jevon C. Hercules
- grid.12916.3d0000 0001 2322 4996Department of Mathematics, University of the West Indies at Mona, Kingston, Jamaica
- grid.12955.3a0000 0001 2264 7233Present Address: Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China
| | - Amna Ansari
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
| | - Ian Brain
- grid.25073.330000 0004 1936 8227Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON Canada
| | - Christine MacColl
- grid.25073.330000 0004 1936 8227Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON Canada
| | - Yili Xu
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Yuxin Jin
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Sharon Chang
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - John D. Carpten
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - André Bédard
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
| | - Greg R. Pond
- grid.25073.330000 0004 1936 8227Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON Canada
- grid.25073.330000 0004 1936 8227Department of Oncology, McMaster University, Hamilton, ON Canada
| | - Kim R. M. Blenman
- grid.433818.5Department of Internal Medicine, Section of Medical Oncology, Yale Cancer Center, School of Medicine, New Haven, CT USA
- grid.47100.320000000419368710Department of Computer Science, School of Engineering and Applied Science, Yale University, New Haven, CT USA
| | - Zarko Manojlovic
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Juliet M. Daniel
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
- African Caribbean Cancer Consortium, Philadelphia, PA USA
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8
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Marczyk M, Gunasekharan V, Casadevall D, Qing T, Foldi J, Sehgal R, Shan NL, Blenman KRM, O'Meara TA, Umlauf S, Surovtseva YV, Muthusamy V, Rinehart J, Perry RJ, Kibbey R, Hatzis C, Pusztai L. Comprehensive Analysis of Metabolic Isozyme Targets in Cancer. Cancer Res 2022; 82:1698-1711. [PMID: 35247885 PMCID: PMC10883296 DOI: 10.1158/0008-5472.can-21-3983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/07/2022] [Accepted: 02/21/2022] [Indexed: 11/16/2022]
Abstract
Metabolic reprogramming is a hallmark of malignant transformation, and loss of isozyme diversity (LID) contributes to this process. Isozymes are distinct proteins that catalyze the same enzymatic reaction but can have different kinetic characteristics, subcellular localization, and tissue specificity. Cancer-dominant isozymes that catalyze rate-limiting reactions in critical metabolic processes represent potential therapeutic targets. Here, we examined the isozyme expression patterns of 1,319 enzymatic reactions in 14 cancer types and their matching normal tissues using The Cancer Genome Atlas mRNA expression data to identify isozymes that become cancer-dominant. Of the reactions analyzed, 357 demonstrated LID in at least one cancer type. Assessment of the expression patterns in over 600 cell lines in the Cancer Cell Line Encyclopedia showed that these reactions reflect cellular changes instead of differences in tissue composition; 50% of the LID-affected isozymes showed cancer-dominant expression in the corresponding cell lines. The functional importance of the cancer-dominant isozymes was assessed in genome-wide CRISPR and RNAi loss-of-function screens: 17% were critical for cell proliferation, indicating their potential as therapeutic targets. Lists of prioritized novel metabolic targets were developed for 14 cancer types; the most broadly shared and functionally validated target was acetyl-CoA carboxylase 1 (ACC1). Small molecule inhibition of ACC reduced breast cancer viability in vitro and suppressed tumor growth in cell line- and patient-derived xenografts in vivo. Evaluation of the effects of drug treatment revealed significant metabolic and transcriptional perturbations. Overall, this systematic analysis of isozyme expression patterns elucidates an important aspect of cancer metabolic plasticity and reveals putative metabolic vulnerabilities. SIGNIFICANCE This study exploits the loss of metabolic isozyme diversity common in cancer and reveals a rich pool of potential therapeutic targets that will allow the repurposing of existing inhibitors for anticancer therapy. See related commentary by Kehinde and Parker, p. 1695.
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Affiliation(s)
- Michal Marczyk
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
- Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland
| | | | - David Casadevall
- Cancer Research Program, Hospital del Mar Research Institute (IMIM), Barcelona, Spain
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
| | - Tao Qing
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Julia Foldi
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Raghav Sehgal
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Naing Lin Shan
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Kim R M Blenman
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Tess A O'Meara
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Sheila Umlauf
- Yale Center for Molecular Discovery, Yale University, West Haven, Connecticut
| | - Yulia V Surovtseva
- Yale Center for Molecular Discovery, Yale University, West Haven, Connecticut
| | - Viswanathan Muthusamy
- Center for Precision Cancer Modeling, Yale School of Medicine, New Haven, Connecticut
| | - Jesse Rinehart
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Rachel J Perry
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Richard Kibbey
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Christos Hatzis
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Lajos Pusztai
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
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9
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Iwase T, Blenman KRM, Li X, Reisenbichler E, Seitz R, Hout D, Nielsen TJ, Schweitzer BL, Bailey DB, Shen Y, Zhang X, Pusztai L, Ueno NT. A Novel Immunomodulatory 27-Gene Signature to Predict Response to Neoadjuvant Immunochemotherapy for Primary Triple-Negative Breast Cancer. Cancers (Basel) 2021; 13:cancers13194839. [PMID: 34638323 PMCID: PMC8508147 DOI: 10.3390/cancers13194839] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 09/24/2021] [Accepted: 09/24/2021] [Indexed: 12/31/2022] Open
Abstract
Simple Summary Through analysis of specimens from patients with primary triple-negative breast cancer (TNBC) enrolled in a neoadjuvant clinical trial assessing durvalumab with chemotherapy, we confirmed a novel 27-gene immuno-oncology (IO) signature that generates an IO score to predict the pathologic complete response (pCR) of primary TNBC to neoadjuvant immunotherapy with the PD-L1 blocker durvalumab with chemotherapy. Combining the 27-gene IO signature with PD-L1 immunohistochemistry strengthened the model’s predictive power of the pCR. Furthermore, the comprehensive computational analysis revealed that the 27-gene IO signature corresponded with an immunogenic tumor microenvironment. Abstract A precise predictive biomarker for TNBC response to immunochemotherapy is urgently needed. We previously established a 27-gene IO signature for TNBC derived from a previously established 101-gene model for classifying TNBC. Here we report a pilot study to assess the performance of a 27-gene IO signature in predicting the pCR of TNBC to preoperative immunochemotherapy. We obtained RNA sequencing data from the primary tumors of 55 patients with TNBC, who received neoadjuvant immunochemotherapy with the PD-L1 blocker durvalumab. We determined the power and accuracy in predicting pCR for the immunomodulatory (IM) subtype identified by the 101-gene model, the 27-gene IO signature, and PD-L1 expression by immunohistochemistry (IHC). The pCR rate was 45% (25/55). The odds ratios for pCR were as follows: IM subtype by 101-gene model, 3.14 (p = 0.054); 27-gene IO signature, 4.13 (p = 0.012); PD-L1 expression by IHC, 2.63 (p = 0.106); 27-gene IO signature in combination with PD-L1 expression by IHC, 6.53 (p = 0.003). The 27-gene IO signature has the potential to predict the pCR of primary TNBC to neoadjuvant immunochemotherapy. Further analysis in a large cohort is needed.
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Affiliation(s)
- Toshiaki Iwase
- Section of Translational Breast Cancer Research, Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA;
| | - Kim R. M. Blenman
- Medical Oncology, Yale Cancer Center, 35 Park Street, North Pavilion 1, New Haven, CT 06511, USA; (K.R.M.B.); (X.L.)
| | - Xiaotong Li
- Medical Oncology, Yale Cancer Center, 35 Park Street, North Pavilion 1, New Haven, CT 06511, USA; (K.R.M.B.); (X.L.)
| | - Emily Reisenbichler
- Pathology Yale Cancer Center, 35 Park Street, North Pavilion 1, New Haven, CT 06511, USA;
| | - Robert Seitz
- Oncocyte Corporation, 15 Cushing, Irvine, CA 92618, USA; (R.S.); (D.H.); (T.J.N.); (B.L.S.); (D.B.B.)
| | - David Hout
- Oncocyte Corporation, 15 Cushing, Irvine, CA 92618, USA; (R.S.); (D.H.); (T.J.N.); (B.L.S.); (D.B.B.)
| | - Tyler J. Nielsen
- Oncocyte Corporation, 15 Cushing, Irvine, CA 92618, USA; (R.S.); (D.H.); (T.J.N.); (B.L.S.); (D.B.B.)
| | - Brock L. Schweitzer
- Oncocyte Corporation, 15 Cushing, Irvine, CA 92618, USA; (R.S.); (D.H.); (T.J.N.); (B.L.S.); (D.B.B.)
| | - Daniel B. Bailey
- Oncocyte Corporation, 15 Cushing, Irvine, CA 92618, USA; (R.S.); (D.H.); (T.J.N.); (B.L.S.); (D.B.B.)
| | - Yichao Shen
- Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA; (Y.S.); (X.Z.)
| | - Xiang Zhang
- Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA; (Y.S.); (X.Z.)
| | - Lajos Pusztai
- Medical Oncology, Yale Cancer Center, 35 Park Street, North Pavilion 1, New Haven, CT 06511, USA; (K.R.M.B.); (X.L.)
- Correspondence: (L.P.); (N.T.U.); Tel.: +1-203-737-8309 (L.P.); +1-713792-8754 (N.T.U.); Fax: +1-888-375-2139 (N.T.U.)
| | - Naoto T. Ueno
- Section of Translational Breast Cancer Research, Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA;
- Correspondence: (L.P.); (N.T.U.); Tel.: +1-203-737-8309 (L.P.); +1-713792-8754 (N.T.U.); Fax: +1-888-375-2139 (N.T.U.)
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10
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Gonzalez-Ericsson PI, Wulfkhule JD, Gallagher RI, Sun X, Axelrod ML, Sheng Q, Luo N, Gomez H, Sanchez V, Sanders M, Pusztai L, Petricoin E, Blenman KRM, Balko JM. Tumor-Specific Major Histocompatibility-II Expression Predicts Benefit to Anti-PD-1/L1 Therapy in Patients With HER2-Negative Primary Breast Cancer. Clin Cancer Res 2021; 27:5299-5306. [PMID: 34315723 DOI: 10.1158/1078-0432.ccr-21-0607] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/15/2021] [Accepted: 07/15/2021] [Indexed: 12/16/2022]
Abstract
PURPOSE Immunotherapies targeting PD-1/L1 enhance pathologic complete response (pCR) rates when added to standard neoadjuvant chemotherapy (NAC) regimens in early-stage triple-negative, and possibly high-risk estrogen receptor-positive breast cancer. However, immunotherapy has been associated with significant toxicity, and most patients treated with NAC do not require immunotherapy to achieve pCR. Biomarkers discerning patients benefitting from the addition of immunotherapy from those who would achieve pCR to NAC alone are clearly needed. In this study, we tested the ability of MHC-II expression on tumor cells, to predict immunotherapy-specific benefit in the neoadjuvant breast cancer setting. PATIENTS AND METHODS This was a retrospective tissue-based analysis of 3 cohorts of patients with breast cancer: (i) primary nonimmunotherapy-treated breast cancers (n = 381), (ii) triple-negative breast cancers (TNBC) treated with durvalumab and standard NAC (n = 48), and (iii) HER2-negative patients treated with standard NAC (n = 87) or NAC and pembrolizumab (n = 66). RESULTS HLA-DR positivity on ≥5% of tumor cells, defined a priori, was observed in 10% and 15% of primary non-immunotherapy-treated hormone receptor-positive and triple-negative breast cancers, respectively. Quantitative assessment of MHC-II on tumor cells was predictive of durvalumab + NAC and pembrolizumab + NAC (ROC AUC, 0.71; P = 0.01 and AUC, 0.73; P = 0.001, respectively), but not NAC alone (AUC, 0.5; P = 0.99). CONCLUSIONS Tumor-specific MHC-II has a strong candidacy as a specific biomarker of anti-PD-1/L1 immunotherapy benefit when added to standard NAC in HER2-negative breast cancer. Combined with previous studies in melanoma, MHC-II has the potential to be a pan-cancer biomarker. Validation is warranted in existing and future phase II/III clinical trials in this setting.
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Affiliation(s)
- Paula I Gonzalez-Ericsson
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Julia D Wulfkhule
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia
| | - Rosa I Gallagher
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia
| | - Xiaopeng Sun
- Program in Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Margaret L Axelrod
- Program in Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Quanhu Sheng
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Na Luo
- Anatomy and Histology, School of Medicine, Nankai University, Tianjin, China
| | - Henry Gomez
- Department of Medical Oncology, Instituto Nacional de Enfermedades Neoplásicas, Lima, Perú
| | - Violeta Sanchez
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Melinda Sanders
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.,Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Lajos Pusztai
- Department of Internal Medicine Section of Medical Oncology and Yale Cancer Center, School of Medicine, Yale University, New Haven, Connecticut
| | - Emanuel Petricoin
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia
| | - Kim R M Blenman
- Department of Internal Medicine Section of Medical Oncology and Yale Cancer Center, School of Medicine, Yale University, New Haven, Connecticut. .,Department of Computer Science, School of Engineering and Applied Science, Yale University, New Haven, Connecticut
| | - Justin M Balko
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee. .,Program in Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee.,Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee
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11
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Blenman KRM, Spidlen J, Parks DR, Moore W, Treister A, Leif R, Bray C, Goldberg M, Brinkman R. ISAC Probe Tag Dictionary: Standardized Nomenclature for Detection and Visualization Labels Used in Cytometry and Microscopy Imaging. Cytometry A 2020; 99:103-106. [PMID: 32881392 DOI: 10.1002/cyto.a.24224] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/18/2020] [Indexed: 01/06/2023]
Abstract
Since the advent of microscopy imaging and flow cytometry, there has been an explosion in the number of probes, consisting of a component binding to an analyte and a detectable tag, to mark areas of interest in or on cells and tissue. Probe tags have been created to detect and/or visualize probes. Over time, these probe tags have increased in number. The expansion has resulted in arbitrarily created synonyms of probe tags used in publications and software. The synonyms are problematic for readability of publications, accuracy of text/data mining, and bridging data from multiple platforms, protocols, and databases for Big Data analysis. Development and implementation of a universal language for probe tags will ensure equivalent quality and level of data being reported or extracted for clinical/scientific evaluation as well as help connect data from many platforms. The International Society for Advancement of Cytometry Data Standards Task Force composed of academic scientists and industry hardware/software/reagent manufactures have developed recommendations for a standardized nomenclature for probe tags used in cytometry and microscopy imaging. These recommendations are shared in this technical note in the form of a Probe Tag Dictionary. © 2020 International Society for Advancement of Cytometry.
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Affiliation(s)
- Kim R M Blenman
- Department of Internal Medicine, Section of Medical Oncology, Yale University, New Haven, Connecticut, USA
| | | | - David R Parks
- Genetics Department, Stanford University School of Medicine, Stanford, California, USA
| | - Wayne Moore
- Genetics Department, Stanford University School of Medicine, Stanford, California, USA
| | - Adam Treister
- Gladstone Institutes, San Francisco, California, USA
| | - Robert Leif
- Newport Instruments, San Diego, California, USA
| | - Chris Bray
- Verity Software House, Topsham, Maine, USA
| | | | | | - Ryan Brinkman
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada.,Cytapex Bioinformatics Inc, Vancouver, British Columbia, Canada
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12
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Kos Z, Roblin E, Kim RS, Michiels S, Gallas BD, Chen W, van de Vijver KK, Goel S, Adams S, Demaria S, Viale G, Nielsen TO, Badve SS, Symmans WF, Sotiriou C, Rimm DL, Hewitt S, Denkert C, Loibl S, Luen SJ, Bartlett JMS, Savas P, Pruneri G, Dillon DA, Cheang MCU, Tutt A, Hall JA, Kok M, Horlings HM, Madabhushi A, van der Laak J, Ciompi F, Laenkholm AV, Bellolio E, Gruosso T, Fox SB, Araya JC, Floris G, Hudeček J, Voorwerk L, Beck AH, Kerner J, Larsimont D, Declercq S, Van den Eynden G, Pusztai L, Ehinger A, Yang W, AbdulJabbar K, Yuan Y, Singh R, Hiley C, Bakir MA, Lazar AJ, Naber S, Wienert S, Castillo M, Curigliano G, Dieci MV, André F, Swanton C, Reis-Filho J, Sparano J, Balslev E, Chen IC, Stovgaard EIS, Pogue-Geile K, Blenman KRM, Penault-Llorca F, Schnitt S, Lakhani SR, Vincent-Salomon A, Rojo F, Braybrooke JP, Hanna MG, Soler-Monsó MT, Bethmann D, Castaneda CA, Willard-Gallo K, Sharma A, Lien HC, Fineberg S, Thagaard J, Comerma L, Gonzalez-Ericsson P, Brogi E, Loi S, Saltz J, Klaushen F, Cooper L, Amgad M, Moore DA, Salgado R. Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer. NPJ Breast Cancer 2020; 6:17. [PMID: 32411819 PMCID: PMC7217863 DOI: 10.1038/s41523-020-0156-0] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Accepted: 03/02/2020] [Indexed: 02/08/2023] Open
Abstract
Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.
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Affiliation(s)
- Zuzana Kos
- Department of Pathology, BC Cancer - Vancouver, Vancouver, BC Canada
| | - Elvire Roblin
- Department of Biostatistics and Epidemiology, Gustave Roussy, University Paris-Saclay, Villejuif, France
- Oncostat U1018, Inserm, University Paris-Saclay, labeled Ligue Contre le Cancer, Villejuif, France
| | - Rim S. Kim
- National Surgical Adjuvant Breast and Bowel Project (NSABP)/NRG Oncology, Pittsburgh, PA USA
| | - Stefan Michiels
- Department of Biostatistics and Epidemiology, Gustave Roussy, University Paris-Saclay, Villejuif, France
- Oncostat U1018, Inserm, University Paris-Saclay, labeled Ligue Contre le Cancer, Villejuif, France
| | - Brandon D. Gallas
- Division of Imaging, Diagnostics, and Software Reliability (DIDSR); Office of Science and Engineering Laboratories (OSEL); Center for Devices and Radiological Health (CDRH), US Food and Drug Administration (US FDA), Silver Spring, MD USA
| | - Weijie Chen
- Division of Imaging, Diagnostics, and Software Reliability (DIDSR); Office of Science and Engineering Laboratories (OSEL); Center for Devices and Radiological Health (CDRH), US Food and Drug Administration (US FDA), Silver Spring, MD USA
| | - Koen K. van de Vijver
- Department of Pathology, University Hospital Antwerp, Antwerp, Belgium
- Department of Pathology, Ghent University Hospital, Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Shom Goel
- The Sir Peter MacCallum Cancer Centre, Melbourne, VIC Australia
- Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria Australia
| | - Sylvia Adams
- Perlmutter Cancer Center, New York University Medical School, New York, NY USA
| | - Sandra Demaria
- Departments of Radiation Oncology and Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY USA
| | - Giuseppe Viale
- Department of Pathology, Istituto Europeo di Oncologia, University of Milan, Milan, Italy
| | - Torsten O. Nielsen
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada
| | - Sunil S. Badve
- Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, USA
| | - W. Fraser Symmans
- Department of Pathology, The University of Texas M.D. Anderson Cancer Center, Houston, TX USA
| | - Christos Sotiriou
- Department of Medical Oncology, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - David L. Rimm
- Department of Pathology, Yale School of Medicine, New Haven, CT USA
| | - Stephen Hewitt
- Laboratory of Pathology, National Cancer Institute, NIH, Bethesda, MD USA
| | - Carsten Denkert
- Institute of Pathology, Universitätsklinikum Gießen und Marburg GmbH, Standort Marburg and Philipps-Universität Marburg, Marburg, Germany
| | | | - Stephen J. Luen
- Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria Australia
- Division of Research and Cancer Medicine, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, VIC Australia
| | - John M. S. Bartlett
- Ontario Institute for Cancer Research, Toronto, ON Canada
- University of Edinburgh Cancer Research Centre, Edinburgh, UK
| | - Peter Savas
- Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria Australia
- Division of Research and Cancer Medicine, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, VIC Australia
| | - Giancarlo Pruneri
- Department of Pathology, IRCCS Fondazione Instituto Nazionale Tumori and University of Milan, School of Medicine, Milan, Italy
| | - Deborah A. Dillon
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA USA
- Department of Pathology, Dana Farber Cancer Institute, Boston, MA USA
| | - Maggie Chon U. Cheang
- Institute of Cancer Research Clinical Trials and Statistics Unit, The Institute of Cancer Research, Surrey, UK
| | - Andrew Tutt
- Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | | | - Marleen Kok
- Department of Medical Oncology and Division of Tumor Biology & Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Hugo M. Horlings
- Department of Pathology, University Hospital Antwerp, Antwerp, Belgium
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Anant Madabhushi
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH USA
- Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH USA
| | - Jeroen van der Laak
- Computational Pathology Group, Department of Pathology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Francesco Ciompi
- Computational Pathology Group, Department of Pathology, Radboud University Medical Center, Nijmegen, Netherlands
| | | | - Enrique Bellolio
- Departamento de Anatomía Patológica, Universidad de La Frontera, Temuco, Chile
| | | | - Stephen B. Fox
- The Sir Peter MacCallum Cancer Centre, Melbourne, VIC Australia
- Department of Pathology, Peter MacCallum Cancer Centre Department of Pathology, Melbourne, VIC Australia
| | | | - Giuseppe Floris
- KU Leuven- Univerisity of Leuven, Department of Imaging and Pathology, Laboratory of Translational Cell & Tissue Research and KU Leuven- University Hospitals Leuven, Department of Pathology, Leuven, Belgium
| | - Jan Hudeček
- Department of Research IT, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Leonie Voorwerk
- Division of Tumor Biology & Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | | | - Denis Larsimont
- Department of Pathology, Jules Bordet Institute, Brussels, Belgium
| | | | | | - Lajos Pusztai
- Department of Internal Medicine, Section of Medical Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT USA
| | - Anna Ehinger
- Department of Clinical Genetics and Pathology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Wentao Yang
- Department of Pathology, Fudan University Shanghai Cancer Centre, Shanghai, China
| | - Khalid AbdulJabbar
- Centre for Evolution and Cancer; Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Yinyin Yuan
- Centre for Evolution and Cancer; Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Rajendra Singh
- Icahn School of Medicine at Mt. Sinai, New York, NY 10029 USA
| | - Crispin Hiley
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, University College London, London, UK
| | - Maise al Bakir
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, University College London, London, UK
| | - Alexander J. Lazar
- Departments of Pathology, Genomic Medicine, Dermatology, and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Stephen Naber
- Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, USA
| | - Stephan Wienert
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| | - Miluska Castillo
- Department of Medical Oncology and Research, Instituto Nacional de Enfermedades Neoplasicas, Lima, 15038 Peru
| | | | - Maria-Vittoria Dieci
- Medical Oncology 2, Istituto Oncologico Veneto IOV - IRCCS, Padova, Italy
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Fabrice André
- Department of Medical Oncology, Institut Gustave Roussy, Villejuif, France
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, University College London, London, UK
- Francis Crick Institute, Midland Road, London, UK
| | - Jorge Reis-Filho
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Joseph Sparano
- Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY USA
| | - Eva Balslev
- Department of Pathology, Herlev and Gentofte Hospital, Herlev, Denmark
| | - I-Chun Chen
- Department of Oncology, National Taiwan University Cancer Center, Taipei, Taiwan
- Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Oncology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | | | - Katherine Pogue-Geile
- National Surgical Adjuvant Breast and Bowel Project (NSABP)/NRG Oncology, Pittsburgh, PA USA
| | - Kim R. M. Blenman
- Department of Internal Medicine, Section of Medical Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT USA
| | | | - Stuart Schnitt
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA USA
| | - Sunil R. Lakhani
- The University of Queensland Centre for Clinical Research and Pathology Queensland, Brisbane, QLD Australia
| | - Anne Vincent-Salomon
- Institut Curie, Paris Sciences Lettres Université, Inserm U934, Department of Pathology, Paris, France
| | - Federico Rojo
- Pathology Department, Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD) - CIBERONC, Madrid, Spain
- GEICAM-Spanish Breast Cancer Research Group, Madrid, Spain
| | - Jeremy P. Braybrooke
- Nuffield Department of Population Health, University of Oxford, Oxford and Department of Medical Oncology, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Matthew G. Hanna
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - M. Teresa Soler-Monsó
- Department of Pathology, Bellvitge University Hospital, IDIBELL. Breast Unit. Catalan Institut of Oncology. L ‘Hospitalet del Llobregat’, Barcelona, 08908 Catalonia Spain
| | - Daniel Bethmann
- University Hospital Halle (Saale), Institute of Pathology, Halle (Saale), Germany
| | - Carlos A. Castaneda
- Department of Medical Oncology and Research, Instituto Nacional de Enfermedades Neoplasicas, Lima, 15038 Peru
| | - Karen Willard-Gallo
- Molecular Immunology Unit, Institut Jules Bordet, Universitè Libre de Bruxelles, Brussels, Belgium
| | - Ashish Sharma
- Department of Biomedical Informatics, Emory University, Atlanta, GA USA
| | - Huang-Chun Lien
- Department of Pathology, National Taiwan University Hospital, Taipei, Taiwan
| | - Susan Fineberg
- Department of Pathology, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY USA
| | - Jeppe Thagaard
- DTU Compute, Department of Applied Mathematics, Technical University of Denmark; Visiopharm A/S, Hørsholm, Denmark
| | - Laura Comerma
- GEICAM-Spanish Breast Cancer Research Group, Madrid, Spain
- Pathology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - Paula Gonzalez-Ericsson
- Breast Cancer Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN USA
| | - Edi Brogi
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Sherene Loi
- Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria Australia
- Division of Research and Cancer Medicine, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, VIC Australia
| | - Joel Saltz
- Biomedical Informatics Department, Stony Brook University, Stony Brook, NY USA
| | - Frederick Klaushen
- Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Lee Cooper
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL USA
| | - Mohamed Amgad
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA USA
| | - David A. Moore
- Department of Pathology, UCL Cancer Institute, UCL, London, UK
- University College Hospitals NHS Trust, London, UK
| | - Roberto Salgado
- Division of Research and Cancer Medicine, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, VIC Australia
- Department of Pathology, GZA-ZNA, Antwerp, Belgium
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13
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Wong PF, Wei W, Smithy JW, Acs B, Toki MI, Blenman KRM, Zelterman D, Kluger HM, Rimm DL. Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes and Immunotherapy Outcome in Metastatic Melanoma. Clin Cancer Res 2019; 25:2442-2449. [PMID: 30617133 PMCID: PMC6467753 DOI: 10.1158/1078-0432.ccr-18-2652] [Citation(s) in RCA: 91] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 10/19/2018] [Accepted: 01/03/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE Because durable response to programmed cell death 1 (PD-1) inhibition is limited to a subset of melanoma patients, new predictive biomarkers could have clinical utility. We hypothesize that pretreatment tumor-infiltrating lymphocyte (TIL) profiles could be associated with response. EXPERIMENTAL DESIGN Pretreatment whole tissue sections from 94 melanoma patients treated with anti-PD-1 therapy were profiled by multiplex immunofluorescence to perform TIL quantification (CD4, CD8, CD20) and assess TIL activation (CD3, GZMB, Ki67). Two independent image analysis technologies were used: inForm (PerkinElmer) to determine cell counts, and AQUA to measure protein by quantitative immunofluorescence (QIF). TIL parameters by both methodologies were correlated with objective response or disease control rate (ORR/DCR) by RECIST 1.1 and survival outcome. RESULTS Pretreatment lymphocytic infiltration, by cell counts or QIF, was significantly higher in complete or partial response than in stable or progressive disease, particularly for CD8 (P < 0.0001). Neither TIL activation nor dormancy was associated with outcome. CD8 associations with progression-free survival (HR > 3) were independently significant in multivariable analyses and accounted for similar CD3 associations in anti-PD-1-treated patients. CD8 was not associated with melanoma prognosis in the absence of immunotherapy. Predictive performance of CD8 cell count (and QIF) had an area under the ROC curve above 0.75 (ORR/DCR), which reached 0.83 for ipilimumab plus nivolumab. CONCLUSIONS Pretreatment lymphocytic infiltration is associated with anti-PD-1 response in metastatic melanoma. Quantitative TIL analysis has potential for application in digital precision immuno-oncology as an "indicative" companion diagnostic.
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Affiliation(s)
- Pok Fai Wong
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Wei Wei
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
| | - James W Smithy
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Balazs Acs
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Maria I Toki
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Kim R M Blenman
- Department of Dermatology, Yale School of Medicine, New Haven, Connecticut
| | - Daniel Zelterman
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
| | - Harriet M Kluger
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
- Section of Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - David L Rimm
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut.
- Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut
- Section of Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
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14
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Blenman KRM, Wang J, Cowper S, Bosenberg M. Pathology of spontaneous and immunotherapy-induced tumor regression in a murine model of melanoma. Pigment Cell Melanoma Res 2019; 32:448-457. [PMID: 30702217 DOI: 10.1111/pcmr.12769] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 12/22/2018] [Accepted: 01/21/2019] [Indexed: 12/15/2022]
Abstract
We evaluated the spontaneous and immunotherapy-induced histological changes in the tumor microenvironment of a mouse melanoma regression model consisting of immunocompetent C57BL/6J mice implanted with syngeneic YUMMER1.7 melanoma cells. We focused on tumor regression phenotypes and spatial relationships of melanoma cells with B cells and neutrophils since this was not previously described. We found common themes to the host response to cancer irrespective of the mode of tumor regression. In nonregression tumors, melanoma cells were epithelioid shaped and tightly packed. In regression tumors, melanoma cells were spindle shaped and discohesive. B cells including plasmablasts and plasma cells were numerous and were increased with immunotherapy. Neutrophils were in direct contact with dead or dying melanoma cells. Immunotherapy increased neutrophil counts and induced neutrophil extracellular traps (NETs)-like formations and geographic necrosis. Beyond tumor regression, the increase in the B cell and neutrophil response could play a role in immunotherapy-induced adverse reactions.
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Affiliation(s)
- Kim R M Blenman
- Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut
| | - Jake Wang
- Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut
| | - Shawn Cowper
- Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut.,Department of Pathology, Yale University School of Medicine, New Haven, Connecticut
| | - Marcus Bosenberg
- Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut.,Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut.,Department of Pathology, Yale University School of Medicine, New Haven, Connecticut
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15
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Blenman KRM, Bosenberg MW. Immune Cell and Cell Cluster Phenotyping, Quantitation, and Visualization Using In Silico Multiplexed Images and Tissue Cytometry. Cytometry A 2018; 95:399-410. [PMID: 30468565 DOI: 10.1002/cyto.a.23668] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 10/02/2018] [Accepted: 10/15/2018] [Indexed: 11/11/2022]
Abstract
Phenotyping immune cells and cell clusters in situ, including their activation state and function, can aid in interpretation of spatial relationships within the tissue microenvironment. Immune cell phenotypes require multiple biomarkers. However, conventional microscopy setups can only image up to four biomarkers at one time. In this report, we describe and give an example of a workflow to phenotype, quantitate, and visualize greater than four biomarkers in silico utilizing multiplexed fluorescence histology and the TissueFAXS quantitative imaging system with a conventional microscopy setup. Biomarkers were conjugated to Cy3 or Cy5. Multiplexed staining was performed on formalin-fixed paraffin-embedded tissue sections. We imaged the slides, inactivated the dyes, and repeated the process until all biomarkers were stained. Phenotype profiles were built based on in silico combinations of the biomarkers. We used algorithms that aligned all images to create a composite image, isolated each cell in the image, and identified biomarker positive cells in the image. The in silico phenotypes were quantitated and displayed through flow cytometry-like histograms and dot scatterplots in addition to backgating into the tissue images. The advantage of our workflow is that it provides visual verification of cell isolation and identification as well as highlight characteristics of cells and cell clusters. © 2018 International Society for Advancement of Cytometry.
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Affiliation(s)
- Kim R M Blenman
- Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Marcus W Bosenberg
- Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut, USA.,Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA.,Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA
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16
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Blenman KRM, He TF, Frankel PH, Ruel NH, Schwartz EJ, Krag DN, Tan LK, Yim JH, Mortimer JE, Yuan Y, Lee PP. Sentinel lymph node B cells can predict disease-free survival in breast cancer patients. NPJ Breast Cancer 2018; 4:28. [PMID: 30155518 PMCID: PMC6107630 DOI: 10.1038/s41523-018-0081-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 07/25/2018] [Accepted: 07/26/2018] [Indexed: 12/31/2022] Open
Abstract
Tumor invasion into draining lymph nodes, especially sentinel lymph nodes (SLNs), is a key determinant of prognosis and treatment in breast cancer as part of the TNM staging system. Using multicolor histology and quantitative image analysis, we quantified immune cells within SLNs from a discovery cohort of 76 breast cancer patients. We found statistically more in situ CD3+ T cells in tumor negative vs. tumor positive nodes (mean of 8878 vs. 6704, respectively, p = 0.006), but no statistical difference in CD20+ B cells or CD1a+ dendritic cells. In univariate analysis, a reduced hazard was seen with a unit increase in log CD3 with HR 0.49 (95% CI 0.30–0.80) and log CD20 with HR 0.37 (95% CI 0.22–0.62). In multivariate analysis, log CD20 remained significant with HR 0.42 (95% CI 0.25–0.69). When restricted to SLN tumor negative patients, increased log CD20 was still associated with improved DFS (HR = 0.26, 95% CI 0.08–0.90). The CD20 results were validated in a separate cohort of 21 patients (n = 11 good outcome, n = 10 poor outcome) with SLN negative triple-negative breast cancer (TNBC) (“good” mean of 7011 vs. “poor” mean of 4656, p = 0.002). Our study demonstrates that analysis of immune cells within SLNs, regardless of tumor invasion status, may provide additional prognostic information, and highlights B cells within SLNs as important in preventing future recurrence. B cells within the tumor-draining lymph nodes may have an important biological role in preventing relapse of breast cancer. A team led by Peter Lee from City of Hope in Duarte, California, USA, quantified the levels of three populations of immune cells—T cells, B cells and dendritic cells—within sentinel lymph nodes biopsied from a cohort of 76 patients. They found that larger numbers of T cells and B cells were both linked to longer progression-free survival in the women. However, after statistically accounting for correlations between the two immune cell types, the researchers concluded that B cells had the dominant beneficial effect on survival times. They validated the finding that high B-cell counts are a prognostic indicator of better outcomes in a separate cohort of 21 women with triple-negative breast cancer.
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Affiliation(s)
- Kim R M Blenman
- 1Department of Immuno-Oncology, City of Hope and Beckman Research Institute, Duarte, CA USA.,8Present Address: Department of Dermatology, Yale University, New Haven, CT USA
| | - Ting-Fang He
- 1Department of Immuno-Oncology, City of Hope and Beckman Research Institute, Duarte, CA USA
| | - Paul H Frankel
- 2Department of Biostatistics, City of Hope and Beckman Research Institute, Duarte, CA USA
| | - Nora H Ruel
- 2Department of Biostatistics, City of Hope and Beckman Research Institute, Duarte, CA USA
| | - Erich J Schwartz
- 3Department of Pathology, Stanford University, Stanford, CA USA.,9Present Address: Department of Pathology, Beaumont Health, Farmington Hills, MI USA
| | - David N Krag
- 4Department of Surgery, University of Vermont College of Medicine, Burlington, VT USA
| | - Lee K Tan
- 5Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - John H Yim
- 6Department of Surgery, City of Hope and Beckman Research Institute, Duarte, CA USA
| | - Joanne E Mortimer
- 7Department of Women's Health, City of Hope and Beckman Research Institute, Duarte, CA USA
| | - Yuan Yuan
- 7Department of Women's Health, City of Hope and Beckman Research Institute, Duarte, CA USA
| | - Peter P Lee
- 1Department of Immuno-Oncology, City of Hope and Beckman Research Institute, Duarte, CA USA
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17
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Riess JW, Bhattacharya N, Blenman KRM, Neal JW, Hwang G, Pultar P, San-Pedro Salcedo M, Engleman E, Lee PP, Malik R, Wakelee HA. Immune correlates of talactoferrin alfa in biopsied tumor of relapsed/refractory metastatic non-small cell lung cancer patients. Immunopharmacol Immunotoxicol 2014; 36:182-6. [PMID: 24494587 DOI: 10.3109/08923973.2013.864671] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
CONTEXT Talactoferrin alfa (TLF) is a unique recombinant form of human lactoferrin. The hypothesized mechanism of action involves TLF binding to the intestinal endothelium inducing dendritic cell maturation and cytokine release leading to infiltration of tumor with monocytes and T-lymphocytes and inhibition of tumor growth. OBJECTIVE Based on promising phase II trial results, this correlative study was undertaken to examine immune mechanism of action of TLF in metastatic non-small cell lung cancer (NSCLC) patients. METHODS Talactoferrin was administered orally at 1.5 g bid weeks 1-12 with 2 weeks off on a 14-week cycle. Enrolled patients had a pathologic diagnosis of NSCLC previously treated with at least two lines of systemic treatment. Patients had core biopsy of tumor before initiation of talactoferrin and at week 7 on TLF. Flow cytometry and quantitative immunohistochemistry for immune correlates were performed on the biopsied specimens. RESULTS Four patients with metastatic NSCLC were enrolled. The trial was halted pre-maturely in light of negative phase III trial results. For the two patients who had repeat on-treatment tumor biopsies, a consistent increase in monocytes as a percentage of total immune cells was observed. Otherwise, no clear trend of increase or decrease was observed in any other immune cell parameters compared to matched patient pre-treatment biopsies. CONCLUSION Repeat biopsies for immune correlates by flow cytometry and quantitative immunohistochemistry in NSCLC patients are feasible. In the few patients sampled before trial closure, increased monocytes as a total percentage of the immune cell population within tumor was observed in response to TLF.
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Affiliation(s)
- Jonathan W Riess
- Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA, USA
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18
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Blenman KRM, Lee PP. Quantitative and spatial image analysis of tumor and draining lymph nodes using immunohistochemistry and high-resolution multispectral imaging to predict metastasis. Methods Mol Biol 2014; 1102:601-621. [PMID: 24259001 DOI: 10.1007/978-1-62703-727-3_32] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Immunohistochemistry is an essential tool for clinical and translational research laboratories. It is mostly used as a qualitative measure of morphology and cell types within tissue. We have developed a high-resolution multispectral imaging method to expand the uses of immunohistochemistry by making it quantitative. In this chapter we describe the technology, both hardware and software, that we use for this method and give examples of applications.
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Affiliation(s)
- Kim R M Blenman
- Cancer Immunotherapeutics & Tumor Immunology, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
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19
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Abstract
Multiple studies have reported high levels of IL-10 in SLE patients and in murine models of lupus. IL-10 is a regulatory cytokine mainly produced by B cells, which use this cytokine to support their proliferation, and by myeloid cells, which use IL-10 to reduce proinflammatory responses. IL-10 is also produced by a subset of CD4+ T regulatory cells. Various manipulations of IL-10 levels with repeated administrations of anti-IL-10 neutralizing antibodies, genetic ablation or injections of recombinant cytokine have shown contradictory results, which is likely to reflect the opposite effects of this cytokine on the two major effector arms of lupus pathologenesis, namely B cells and inflammation. We have investigated the role of IL-10 in a novel congenic model of lupus, B6.Sle1.Sle2.Sle3 (B6.TC), which consists of the three NZM2410-derived SLE susceptibility loci combined on a C57BL/6 background. We first investigated in this model the source of elevated IL-10 and shown that it results from a larger number of CD4+ T cells producing the cytokine, and from a greatly increased B1-a cell pool, which is the main IL-10 producing compartment. We have then used AAV-mediated skeletal muscle gene delivery to overexpress IL-10 in young B6.TC mice and follow disease marker expression up to 7 months of age. We show here that continuous overexpression of low levels of IL-10 significantly delayed antinuclear auto-antibody production and decreased clinical nephritis. B cell phenotypes were largely unaffected, while T-cell activation was significantly reduced. This highlighted the pivotal role played by T-cell activation in this model, and suggested that this pathway could be effectively targeted for therapeutic interventions. These results also reinforce the notion that IL-10 exerts multiple functions and commend caution in equating high levels of IL-10 and increased pathogenesis in systemic autoimmunity.
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Affiliation(s)
- Kim R M Blenman
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL 32601-0275, USA
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20
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Blenman KRM, Bahjat FR, Moldawer LL, Morel L. Aberrant signaling in the TNFα/TNF receptor 1 pathway of the NZM2410 lupus-prone mouse. Clin Immunol 2004; 110:124-33. [PMID: 15003809 DOI: 10.1016/j.clim.2003.09.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2003] [Accepted: 09/16/2003] [Indexed: 10/26/2022]
Abstract
The purpose of this study was to evaluate the ability to induce TNFalpha-dependent apoptosis in vivo in predisease lupus-prone NZM2410 and derived B6.NZM congenic mouse strains. An endotoxicosis model that utilizes LPS and d-galactosamine to induce mortality by TNFalpha/TNFR1-dependent hepatocyte apoptosis was used to assess TNFalpha production, apoptotic signaling, and effects on the production of IL-6 and IL-10. NZM2410 was found to be resistant to endotoxicosis and to produce significantly less TNFalpha-induced IL-6 and IL-10. At low doses of LPS, partial resistance was associated with the Tnfa(w) allele. At higher doses of LPS, partial resistance cosegregated with lupus-susceptibility loci and functionally mapped downstream of caspase 3. Additional partial resistance in NZM2410 was also found upstream of FADD. These results demonstrate the existence of multiple defects in the TNFalpha/TNFR1 signaling pathway in the NZM2410 mouse and their relevance to lupus pathogenesis is discussed.
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Affiliation(s)
- Kim R M Blenman
- Department of Pathology, University of Florida, Gainesville, FL 32610, USA
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